Baseball Betting Strategy: Using the Right Stats to Handicap Baseball Games
Betting Baseball: Betting on Totals (Part 2)
Using the Right Stats to Handicap Baseball Games
by Badger of Predictem.com
Since weve covered the weather and its affects in part one, now
lets take a look at the never-ending and highly debatable discussion
about which stats you should use to handicap baseball games when
youre betting totals.
Whether you are a sabermatrician or just some guy watching baseball and drinking beer, everyone uses some form of statistical data to
enhance their handicapping of baseball. Thats what baseball is all
From the archaic (ERA) to the most hard-core advanced stuff (O-swing %-percentage of pitches outside the strike zone a player swings at),
there are over 100 different statistical categories to use to
handicap a baseball player/pitcher if you would so choose. And thats
just the quantifiable stuff, never mind the contract year, nagging
wife at home because of the drinking issue after games side
distractions that are impossible to turn into a math equation.
How you decide to tap dance through that statistical mine field is up
to you and your personal preference, but here are a few of the ones I
like to use when Im looking specifically at betting a total for the
game. For ease Ill break them into four broad categories: pitching,
hitting, ballpark and umpire statistics. Ranking them from what I
consider most important to least.
Baseball is about history, and its because of the history that a
majority of the mainstream media still use the earned run average
(ERA) as a relevant stat anymore. If you still use a pitchers ERA
when deciding whether or not to bet on a total, dont. There are so
many better stats at your disposal.
If you still want to keep it somewhat simple (using an ERA is insane as well as simple), look at a pitchers WHIP and HR/9 instead.
Their WHIP, or walks plus hits divided by innings pitched, will let
you know if they are throwing strikes (as close to 1.0 as possible)
or if he is putting runners on base and flirting with disaster (1.5
is about as bad as it gets). While their HR/9 is exactly what it
looks like, the number of homeruns per 9 innings pitched they give
up. Obviously, the lower the number (last year Chris Carpenter led
MLB at 0.3) the less likely that pitcher gives up gopher balls (like
Braden Looper at 1.8 in 2009).
If you invest more time looking at the pitchers splits, looking in
specific areas for glaring differences in things like: home vs. away,
day/night, run support and groundball/flyball ratios (GB/FB) relative
to the park theyre pitching in that night. You can find guys that
have huge run support, or that are absolutely terrible during the
day, or that just seem to dominate certain teams (i.e. Astros
Roy Oswalt vs. the Reds) if you look in the right places to find
those kinds of nuggets. If you can find a fly ball pitcher in a small
ballpark, or a groundball guy in a spacious one, its another way to
gain perspective on a wager.
Beyond the obvious runs per game and team batting average, the amount
of hitting statistics you could use to handicap a game in regards to
runs and totals borders on minutia. You could easily go insane and
get paralysis by analysis.
Its also hardly a secret these days which teams in baseball have the high-scoring lineups. You see all of the homeruns and highlights on
SportsCenter each night, so just having a solid knowledge base of
each teams lineup and its realistic potential is often enough to go
by for me.
I used to dig for more, looking at things like batting average with
runners in scoring position, on-base plus slugging percentage (OPS)
and other more advanced stats, but I stopped putting forth as much
effort for one reason.
Major league ball players are some of the streakiest athletes around.
Think about it, how often has your favorite teams entire lineup gone cold for more than a game or two? Or how many times has that same
team won a series on getaway day midweek, only to catch a huge break
by not having to face the next opponents ace in the next series
because hes already pitched?
Those types of scenarios are more important in many cases, and
knowing which teams are hot and cold is part of following the sport
and your daily perusing through the box scores.
The third category of statistics Ill look at when handicapping a
baseball game for a total is the ballpark itself. With another new
ballpark opening up again this season (2010) (Minnesota Twins Target Field),
this is one of the few areas where oddsmakers in Las Vegas are still
learning as they go along with you, offering you a great chance to
find an overlooked angle every now and then.
Last year everyone who paid attention noticed quickly that new Yankee
Stadium was a bandbox, yielding the most homeruns (237) of any park
in the league. Bet the over every time, right?
But if youre a fan of some Park Factors stats, you would also know
that new Yankee Stadium gave up nearly the same rate of homeruns as
Angel Stadium of Anaheim (1.26 to 1.22) and actually finished 20th in
run/rate (.965) ranking it in the lower half of the league and almost
making it a pitchers park. (Park Factors tries to compare the rate
of stats at home vs. the rate of stats on the road.)
Knowing that some parks consistently have higher runs per game
(Baltimore, Colorado, Texas, Boston) is not so much a secret anymore.
But finding the right combination of flyball pitcher, in a small
ballpark like Fenway, with a predominantly left-field pull lineup of
right-handed hitters on a windless night in the high 70s is where you
should be trying to take advantage of the oddsmakers error.
If some handicappers didnt base a large portion of their advanced
analysis on who is calling the balls and strikes, then they wouldnt
keep umpire stats now would they? I personally put about as much
weight on the umpire as I do they weather I like to know who is
behind the plate but its not necessarily going to make or break my
wager on a total.
Guys like Jeff Nelson, Jim Reynolds, Tim Tschida and Tim McClelland are known for having tight strike zones, and are therefore likely to
go over (Reynolds 18-11 O/U in 09; Reynolds 18-11; Tschida 18-11;
McClelland 20-13) and have higher runs per game averages (all four
guys 10 runs or higher) than guys with wider pitcher-friendly zones
(like John Hirschbeck, Jeff Kellogg, Phil Cuzzi and Brian Runge).
You can find an advantage every now and then, but youll go hungry
waiting around to find a pitchers ump with two aces on the bump that
the boys in Vegas havent already found before they set the line.
The bottom line is that there is so much data for you to use, how you
choose to use it is up to you. Just keep in mind that if stats told
the whole truth, every statistician would be rich from breaking the
bank at Vegas. The game is still played by humans, which means that
you still have to bet like a human and go with your gut more often
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